As articulated by Eric Ries in 'The Lean Startup,' raw speed of shipping is meaningless if you're building in the wrong direction. The true measure of progress is how quickly a team can validate assumptions and learn what customers want, which prevents costly rework.
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The goal of early validation is not to confirm your genius, but to risk being proven wrong before committing resources. Negative feedback is a valuable outcome that prevents building the wrong product. It often reveals that the real opportunity is "a degree to the left" of the original idea.
For early-stage AI companies, performance should be measured by the speed of iteration, shipping, and learning, not just traditional metrics like revenue. In a rapidly evolving landscape, the ability to quickly get signals from the market and adapt is the primary indicator of future success.
Since startups lack infinite time and money, an investor's key diligence question is whether the team can learn and iterate fast enough to find a valuable solution before resources run out. This 'learning velocity' is more important than initial traction or a perfect starting plan.
Measuring engineering success with metrics like velocity and deployment frequency (DORA) incentivizes shipping code quickly, not creating customer value. This focus on output can actively discourage the deep product thinking required for true innovation.
Don't treat validation as a one-off task before development. The most successful products maintain a constant feedback loop with users to adapt to changing needs, regulations, and tastes. The worst mistake is to stop listening after the initial launch, as businesses that fail to adapt ultimately fail.
Out of ten principles, the most crucial are solving real user needs, releasing value in slices for quick feedback, and simplifying to avoid dependencies. These directly address the greatest wastes of development capacity: building unwanted features and getting stalled by others.
The firm distinguishes between speed (magnitude) and velocity (magnitude plus direction). Founders are encouraged to focus on velocity, ensuring the entire team is moving quickly *in the right direction*. This prevents wasted effort where mere motion is mistaken for progress, a common trap in turbulent markets.
Founders embrace the MVP for their initial product but often abandon this lean approach for subsequent features, treating each new development as a major project requiring perfection. Maintaining high velocity requires applying an iterative, MVP-level approach to every single feature and launch, not just the first one.
While moats like network effects and brand develop over time, the only sustainable advantage an early-stage startup has is its iteration speed. The ability to quickly cycle through ideas, build MVPs, and gather feedback is the fundamental driver of success before achieving scale.
The misconception that discovery slows down delivery is dangerous. Like stretching before a race prevents injury, proper, time-boxed discovery prevents building the wrong thing. This avoids costly code rewrites and iterative launches that miss the mark, ultimately speeding up the delivery of a successful product.
